KARST: Predicting flow and transport in complex Karst systems

Project Information

KARST

Grant agreement ID: 101071836

DOI

10.3030/101071836

EC signature date 8 March 2023

Start date 1 May 2023

End date 30 April 2029

Funded under

• European Research Council (ERC)

Total cost

€ 9 884 611,25

EU contribution

€ 9 884 611,00

Coordinated by

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
Spain

Periodic Reporting for period 2 - KARST (KARST: Predicting flow and transport in complex Karst systems)

Reporting period: 2024-11-01 to 2026-04-30

Summary of the context and overall objectives of the project

Karst aquifers are a treasure and a threat: while up to 25 percent of the world population depends on them for drinking water, they also have capabilities for extremely fast conduction of water and contaminants. In the light of climate change, we need to prepare for extreme flooding and understand the consequences for karst aquifers. Despite their socio-economic importance, decades of research, and high-profile disasters, karst structures and processes remain notoriously difficult to assess. Because of the complexity of karst and its hidden nature, the foundations of flow and transport models in karst systems are weak. Key phenomena related to extreme events such as flash floods and heavy tails in tracer recovery are still beyond current modeling capabilities. KARST will establish the next generation of coupled stochastic modeling frameworks to predict karst processes, assess the vulnerability of karst aquifers, and forecast their response to extreme events. Our approach will bridge structures and processes on all scales, far beyond the capabilities of current theories and computer simulations. This will be achieved by targeting three key objectives: (i) Identification and quantification of flow and transport at the conduit scale. (ii) Characterization and modeling of karst network structure at the catchment scale. (iii) Derivation of a new upscaled approach to predict karst processes at different resolution scales. Together, this will result in an unprecedented multiscale modeling framework for the prediction of flow and transport in karst.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

KARST progresses in all work packages and tasks as planned. In WP1, UNINE has continued scanning individual karst geometries and thus extended the LIDAR data base. INRIA progressed with the 3D printing of cave models for the laboratory experiments and fabricated a total of 6 cave models according to the LIDAR scans and 2 cave models with idealized random and periodic geometries. IFPEN has validated the experimental setup for turbulent and laminar flow experiments, and installed and tested the setup for particle imaging velocimetry and particle tracking velocimetry. Experiments have been performed for regular pipes, wavy pipe geometries and two cave models. CSIC has implemented an immersed boundary method to numerically represent complex cave wall geometries, and a random walk particle tracking simulator. It has performed direct numerical simulations for laminar and turbulent flows in wavy pipe geometries and in real cave geometries, as well as particle tracking on wavy pipe geometries. In WP2, UNINE has continued collecting data sets of karst network maps from around the world (>100 networks world-wide, the currently largest karst network data base in the world). UNINE has continued advancing in karst simulation and characterization together with UL. In WP3, CSIC has developed the first dedicated simulator for laminar and turbulent flow in karst networks under pressurized and unsaturated flow conditions (https://openkarst.org). IFPEN and CSIC have progressed in the characterization and upscaling of network flow network simplification, and started the systematic quantification and upscaling of network scale flow. In WP 4, IFPEN has initiated work on flood prediction, UNINE in collaboration with CSIC have initiated the modelling of a karst aquifer in Switzerland based on the openKARST model, UL, IFPEN and CSIC have been working on the emergence of karst structure using both numerical models and analogue experiments.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

In the following, we summarize the main results during the first 36 months.
 
WP1:
 
•    Unprecedented inventory of three-dimensional cave geometries at the conduit scale
•    Critical Reynolds number for transition to turbulent flow conditions decreases with increasing aperture variability.
•    Colebrook-White model and similar cannot be used for flow parameterization in strongly variable conduits.
 
WP2:
 
•    Unprecedented data set of karst network geometries worldwide
•    Novel simulator for stochastic karst networks based on combination of GraphRNN and GraphDDPM
•    Novel approaches for karst network classification based on combined graph theoretical and speleogenetical approach.
 
WP3:
 
•    Fully coupled non-linear network flow simulator for pressurized-open-channel flow under laminar and turbulent flow conditions
•    Network scale pressurized flow can be quantified by an effective friction factor that depends on the network heterogeneity
•    Network scale transport can be predicted by a stochastic time-domain random walk model in terms of the flow statistics under laminar and turbulent flow conditions.